Scope - Cureus Journal of AI-Augmented Research
Cureus Journal of AI-Augmented Research (CJAI), a Springer Nature journal, is a peer-reviewed open access platform dedicated to advancing interdisciplinary research in artificial intelligence and augmented research across science, technology, industry, and society. CJAI supports equitable and inclusive publishing for both emerging and established researchers, and publishes high-quality original research, reviews, case studies, editorials, letters, and business reports following rigorous single-blind peer review. The journal welcomes research on AI methodologies, tools, algorithms, and AI-enabled workflows, as well as studies evaluating the real-world impact of AI across domains including healthcare, climate science, materials research, education, policy, and social sciences. CJAI also encourages research in AI ethics, governance, sustainability, equity, workforce transformation, and societal impact, with emphasis on rigorous, reproducible, and practically relevant research that advances responsible AI adoption.
Please refer to the Inclusion and Exclusion Criteria below:
| In Scope: AI is Central | Out of Scope: AI is Peripheral |
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For a detailed overview of research domains and thematic areas covered by the journal, please explore the scope of categories in the sections below:
AI Methods in Research
- Machine Learning
- Deep Learning
- Generative AI
- Natural Language Processing (NLP)
- Explainable AI (XAI)
- Responsible AI
- Large Language Models (LLMs) in Research
- Retrieval-Augmented Generation (RAG)
- Multimodal AI in Research
- Agentic AI for Scientific Discovery
- Multi-Agent AI Frameworks
- Human-in-the-Loop AI Systems
- Autonomous Research Pipelines
- AI for Systematic and Scoping Reviews
- Prompt Engineering for Research
- Foundation Model Fine-Tuning for Research
- Scientific Large Language Models (Sci-LLMs)
- Diffusion Models in Research
- Vision-Language Models (VLMs)
- Tool-Augmented AI Agents
- Small Language Models in Resource-Limited Research
- Neurosymbolic AI for Scientific Reasoning
- Reinforcement Learning in Research Contexts
- Multimodal Data Fusion in Science
Ethics, Governance, and Policy
- AI Ethics
- AI Governance
- Algorithmic Fairness
- Privacy-Preserving Systems
- Ethical Frameworks for AI in Research
- Institutional AI Research Policies
- National and International AI Research Governance
- AI and Research Misconduct
- Algorithmic Accountability in Research
- AI in Research Participant Consent
- AI in Vulnerable Population Research
- Conflicts of Interest in AI Research
- Equity in AI Research Tool Access
- Intellectual Property in AI Research Outputs
- AI and Academic Integrity
- Environmental Sustainability of AI Research
- Global Governance of AI in Science
- AI and the Future of Peer Review
Human-AI Collaboration
- Human-AI Collaboration
- Human-Centered Design
- Cognitive Interaction
- Augmented Cognition
- Intelligent Interfaces
- Mental Models
- Behavior Change
- Self-Reflection Research
- Cognitive Psychology
- Practitioner-AI Collaboration in Applied Research
- Cross-Sector Human-AI Research Teams
- Community and Participatory Research with AI
- Power Dynamics in Human-AI Collaboration
- Human Verification of AI Research Outputs
Research Data and Reproducibility
- Data Augmentation in Scarce-Data Domains
- Reproducibility of AI-Augmented Studies
- Preregistration of AI Studies
- Open Datasets for AI Research
- Open Code and Computational Reproducibility
- Model Cards and Research AI Documentation
- Benchmarking AI Research Tools
- Negative and Null Results
- Adversarial Testing of AI Findings
- Information Retrieval
- Semantic Search
- Automated Summarization
Emerging and Interdisciplinary Frontiers
- Agentic Science and Autonomous Scientific Method
- Metascience – Studying AI Research with AI
- AI in Open Science Movements
- AI in Democratisation of Research
- AI-Enabled Preprint and Rapid Dissemination Culture
- AI for Sustainable Development Goals (SDGs)
- AI in Crisis and Emergency Research
- Quantum-Classical Hybrid AI in Research
- Brain-Computer Interface Research with AI
- AI in Cross-Sector Knowledge Transfer
AI Impact on Research Practices
- Workflow and Productivity Impacts of AI
- AI Adoption Barriers and Facilitators
- AI and Scientific Monoculture
- Open Science and AI Infrastructure
- Compute Access and Research Equity
- Industry vs. Academia in AI Research Capacity
- Environmental Costs of AI in Research
- AI and Commercialisation of Research
- Regional Variation in AI Research Adoption
Validation and Methodological Integrity
- AI vs. Traditional Method Comparisons
- Validation Frameworks for AI Research Tools
- Methodological Innovation in AI Research
- Explainable AI (XAI) in Research
- Uncertainty Quantification in AI Findings
- Hallucination Detection in Research AI
- AI Bias Assessment in Research
Practitioner and Professional Research
- Practitioner Research Methods Using AI
- Translational Research Enabled by AI
- Professional Knowledge Creation Using AI
- Quality Improvement Research Using AI
- AI in Continuing Professional Development
Education and Learning Technologies
- EdTech
- Intelligent Tutoring Systems
- Learner Analytics
- Assistive Writing Technologies